Capacity optimization strategy for energy storage system to ensure power supply

Photovoltaic (PV) and wind power generation are very promising renewable energy sources, reasonable capacity allocation of PV-wind complementary energy storage (ES) power generation system can improve the economy and reliability of system operation. In this paper, the goal is to ensure the power supply of the system and reduce the operation cost. The PV, wind and ES system models are analyzed. The differential evolutionary (DE) algorithm is adopted to optimize the particle swarm optimization (PSO) algorithm, and the parameters of the PSO algorithm are changed through the DE algorithm to obtain better performance. We use MATLAB to verify that when the system is composed of 100kW PV and 100kW wind power, the battery capacity obtained by PSO algorithm is 400kWh, while the algorithm proposed in this paper only requires 330kWh. although the loss of load probability of the system is improved by about 0.12%, the cost is saved by 17.5%. To improve the system operation reliability, we recommend increasing PV, wind and ES capacity at the same time rather than increasing ES capacity separately.